Bovine Subclinical Ketosis in Dairy Herds in Iran

Sakha, Mehdi; Ameri, Mehrdad; Sharifi, Hamid; Taheri, Iman

doi:10.1007/s11259-007-0053-0

Cited by 23 publications

(13 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Cut‐points used to identify subclinical ketosis have ranged from 1.0 to 1.4 mmol/L for blood, serum and plasma BHB concentrations . The prevalence of subclinical ketosis was high in the current population of cattle, with 20% having a serum BHB ≥ 1.4 mmol/L.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of a point‐of‐care electrochemical meter to detect subclinical ketosis and hypoglycaemia in lactating dairy cows

et al. 2017

View full text Add to dashboard Cite

The electrochemical meter provided a clinically useful method to detect subclinical ketosis and hypoglycaemia in lactating dairy cows. Compared with other method validation studies using the meter, we attributed the improved performance of the electrochemical meter to application of a fixed volume of blood (20 μL) to the reagent strip, use of the meter in hot ambient conditions and use of glucose oxidase as the reference method for glucose analysis.

show abstract

Section: Discussionmentioning

confidence: 99%

Evaluation of a point‐of‐care electrochemical meter to detect subclinical ketosis and hypoglycaemia in lactating dairy cows

et al. 2017

View full text Add to dashboard Cite

show abstract

“…Sakha et al (2007) reported lower serum glucose concentrations for cows with sub-clinical ketosis than healthy cows, whereas other researchers observed no association between glucose in blood and risk of disease (i.e., LDA and ketosis) and culling during the postpartal period (Stengärde et al, 2010;Seifi et al, 2011). In the present study, the development of sub-clinical diseases was not evaluated and the incidence of LDA and clinical ketosis was low due to our strict focus on the development of primary diseases during early lactation (i.e., not the development of a disease as a secondary health problem).…”

Section: Metritismentioning

confidence: 99%

Generation of an index for physiological imbalance and its use as a predictor of primary disease in dairy cows during early lactation

Moyes¹,

Larsen

Ingvartsen

2013

Journal of Dairy Science

View full text Add to dashboard Cite

Physiological imbalance (PI) is a situation in which physiological parameters deviate from the normal and cows consequently have an increased risk of developing production diseases and reduced production or reproduction. The objectives of this work were (1) to generate an index for PI based on several plasma metabolites and (2) to compare the use of this index with calculated energy balance (EBAL) and individual plasma metabolites in relation to risk of disease during early lactation. We used a total of 634 lactations from 317 cows consisting of 3 breeds ranging from a parity of 1 to 4. Weekly blood samples were analyzed for selected metabolites; that is, urea nitrogen, albumin, cholesterol, nonesterified fatty acids (NEFA), glucose, and β-hydroxybutyrate (BHBA). Energy intake and EBAL were calculated; veterinary treatment records and daily composite milk somatic cell counts were used to determine incidence of disease. Data were adjusted for numerous fixed effects (e.g., parity, breed, and week around calving) before further statistical analysis. The time of disease (TOD) was recorded as the day in which the signs of disease were observed (TOD=0). The week before and after TOD was ± n wk relative to TOD=0. Each week, all plasma metabolites were individually adjusted to an overall mean (=0) and variance (=1). The normalized variables were included in regression analyses by week of lactation to identify metabolites that explain the variation in calculated EBAL, as a reflection of degree of PI. Nonesterified fatty acids, BHBA, and glucose were weighted within each week based on regression coefficients (i.e., x1-x3 below) generated from a model to predict EBAL. Data from wk -1 relative to TOD were analyzed using a mixed linear model to relate degree of PI and metabolites in blood to risk of disease. The weekly PI index was defined as PI=(x1 × [NEFA])+x2 × [BHBA] - x3 × [glucose])/3. For diseases that developed ≥ 2 wk after calving, no variables were associated with risk of disease. Prepartal PI and plasma NEFA were better predictors of disease (i.e., metritis, retained placenta, and milk fever) at wk 1 than EBAL and plasma BHBA and glucose. Examining the relationship between PI and milk constituents is needed for the development of an automated in-line and real-time surveillance system for early detection of risk animals on-farm.

show abstract

“…The threshold values for BHBA in serum or plasma of cows suffering from SCK has been defined either as 1.2 mmol/L or 1.4 mmol by different researchers [6,14,16,17,19]. The proportion of cows diagnosed with SCK was lower in this study compared to others [2,16,21,23] which showed that SCK was not a serious problem in the farms studied.…”

Section: Discussionmentioning

confidence: 58%

“…The gold standard diagnostic test for SCK is measuring BHBA concentration in serum or plasma because it is stable [13,17,18]. Threshold values of either 1.2 mmol/L [19,20] or 1.4 mmol/L [6,12,16,17] of BHBA in serum or plasma have been recommended to distinguish between normal and cows suffering from SCK. Measuring serum concentration of BHBA is useful for examining individual cows, evaluating herd health and monitoring feeding management [21].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of a Hand-Held Meter to Detect Subclinical Ketosis in Dairy Cows

Xu¹,

Wu²,

Zou³

et al. 2017

J Adv Dairy Res

View full text Add to dashboard Cite

The objective of this study was to evaluate the performance of a new cowside test in detecting sub-clinical ketosis (SCK) by comparing β-hydroxybutyrate (BHBA) concentrations obtained using a new hand-held meter, TNN (Yicheng Co., Beijing, China), with those obtained from the conventional laboratory method and to compare the accuracy of using blood, urine and milk samples for diagnostic purposes. TNN is based on an enzymatic electrochemical technique to detect SCK in dairy cows. 297 samples of blood, 97 samples of urine and 85 samples of milk from clinically healthy Holstein cows from d 1 to 58 post-partum were analyzed. The correlation coefficients for BHBA with TNN versus laboratory method were 0.98. Based on Bland-Altman plot, agreement between the two methods was good for BHBA. In this study, the TNN test had sensitivities of 91.4 and 96.8% at 1.2 and 1.4 mmol of BHBA/L, respectively of whole blood. While the specificities were 97.3% and 98.5%, at 1.2 and 1.4 mmol of BHBA/L, respectively. When compared with TNNthe sensitivities and specificities of urine and milk tests were lower. The sensitivities and specificities were 57 and 80% for milk tests, respectively, and 71% and 94% for urine tests, respectively, when 1.2 mmol/L of blood was defined as the threshold. Raising the threshold of laboratory method to 1.4 mmol/L, the sensitivities and specificities was 75 and 79% for milk tests, and 75 and 93% for urine tests, respectively. We concluded that TNN was a useful tool in diagnosis of SCK and blood tests were better than urine and milk tests.

show abstract

Bovine Subclinical Ketosis in Dairy Herds in Iran

Cited by 23 publications

References 22 publications

Evaluation of a point‐of‐care electrochemical meter to detect subclinical ketosis and hypoglycaemia in lactating dairy cows

Evaluation of a point‐of‐care electrochemical meter to detect subclinical ketosis and hypoglycaemia in lactating dairy cows

Generation of an index for physiological imbalance and its use as a predictor of primary disease in dairy cows during early lactation

Evaluation of a Hand-Held Meter to Detect Subclinical Ketosis in Dairy Cows

Contact Info

Product

Resources

About